Frequency assignment for multi-cell IEEE 802.11 wireless networks

ABSTRACT

A frequency planning method for use in an IEEE 802.11 wireless network is described. The frequency planning method obtains traffic load information associated with access points belonging to a multi-cell wireless network and assigns channels to the access points based on the traffic load information.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a continuation of U.S. patent application Ser. 10,288,041, filedNov. 5, 2002 now abandoned. This application claims the benefit of U.S.Provisional Patent Application Ser. No. 60/337,694, filed Nov. 8, 2001,which is incorporated herein by reference in its entirety for allpurposes.

BACKGROUND

The invention relates to frequency planning for wireless networks.

To meet the growing demand for wireless data services, many companieshave started deploying wireless local area networks (WLANs) in airports,hotels, convention centers, coffee shops and other locations in whichnetwork access by the public is desirable. Many of these WLANs supportthe popular IEEE standard for wireless Local Area Network (LAN)protocol, known as the IEEE 802.11 standard. The IEEE 802.11 standardincludes a medium access control (MAC) layer and several physicallayers, including a frequency-hopping spread spectrum (FHSS) physicallayer and a direct sequence spread spectrum (DSSS) physical layer.Versions of the IEEE 802.11 standard include the IEEE 802.11a standard,which describes a physical layer based on orthogonal frequency divisionmultiplexing (OFDM), and the IEEE 802.11b standard, which specifies ahigh-rate DSSS layer. Because of its maturity and low cost, IEEE 802.11bcapability has been included as standard equipment in many laptopcomputers and hand-held devices. Thus, IEEE 802.11b products make up thebulk of the installed base of IEEE 802.11 systems. The IEEE 802.11 WLANssupport data rates up to 11 Mbps, albeit over short ranges, farexceeding that to be offered by the third generation (3G) cellularwireless networks.

The IEEE 802.11 WLANs and 3G networks (or conventional cellular wirelessnetworks) have major differences in their design at physical (PHY) andmedium access control (MAC) layers to meet different needs. In general,the IEEE 802.11 design is much simpler than that of the 3G networkbecause the IEEE 802.11 standard was devised to serve a confined area(e.g., a link distance of at most several hundred meters) withstationary and slow-moving users, while the 3G specifications weredeveloped for greater flexibility in terms of geographical coverage andmobility, even providing for users traveling at a high speed. As aresult, the IEEE 802.11 network can support data rates higher than thoseby the 3G networks. In addition, the cost of IEEE 802.11 equipment ismuch lower than that for 3G equipment because of the simple and opendesign of IEEE 802.11 networks, coupled with competition among WLANvendors.

In terms of operations, the 3G spectrum (such as the PersonalCommunications System (PCS) band at 1.9 GHz) is licensed and veryexpensive. As a result, every effort has been directed toward optimizingthe spectral efficiency while maintaining the quality of service interms of coverage and data rate for a limited spectrum allocation. Incontrast, the IEEE 802.11b networks operate in the unlicensedIndustrial, Scientific and Medical (ISM) band at 2.4 GHz. Since thefrequency band is free, there is apparently no pressing need to optimizethe spectral efficiency. Rather, simplicity and achieving low cost forthe equipment are more important. Despite the relatively abundantspectrum (i.e., a total of 75 MHz in the 2.4 GHz Band) at the ISM band,as IEEE 802.11b networks are deployed widely, they start to interferewith each other. Such interference leads to a degradation in networkthroughput.

Frequency planning, i.e., allocation of a limited number of frequencies,for an IEEE 802.11b network is different from that for a traditionalcellular network. Frequency planning techniques for cellular wirelessnetworks are well known. In typical cellular wireless networks, such asthose based on the Global System for Mobile Communications (GSM) andEnhanced Data GSM Evolution (EDGE) standards, two separate radiochannels, namely the traffic and control channels, are used to carryuser data and control traffic, respectively. For example, terminalsaccess the control channels to send control information via somecontention mechanism. After the information is successfully received andprocessed by a base station (BS), the terminal is assigned with aspecific traffic channel for transmitting its data traffic. Existingfrequency assignment or radio-resource allocation schemes were devisedmainly for such traffic channels. Such schemes seek to avoid mutualinterference among various terminals or BSs using the same frequency. Inpractical networks, there is no real-time coordination among BSs in theassignment of traffic channels to terminals in different cells. Thus,frequency assignment or radio-resource allocation is based onstatistical averages or worst cases, e.g., 90% chance of acceptable linkquality, across multiple co-channel cells. Typically, frequency planningmechanisms for traditional cellular networks tend to assign the samefrequency to cells that are a sufficient distance apart.

There is no such distinction between control and traffic channels in theIEEE 802.11b network. Instead, all user data and control information (inboth directions between terminals and APs) are carried on the samephysical channel. The access to the channel by multiple transmitters iscoordinated by the MAC protocol, e.g., the well-known, Carrier SenseMultiple Access (CSMA) protocol with collision avoidance feature. Underthat protocol, a transmitter can transmit only if it senses that thechannel is currently idle. As a result, even if two closely located APsare allocated with the same frequency channel, much of the mutual(co-channel) interference can still be avoided by the CSMA protocol, andthe available bandwidth is shared implicitly between the two cellsserved by the two APs. In a sense, the MAC protocol provides aneffective, distributed mechanism to “coordinate” the channel accessamong terminals and APs. In the worst case, both APs behave as if theyshare the same frequency. Nevertheless, the IEEE 802.11 protocol stillworks properly, thus demonstrating the robustness of its design, at theexpense of increased delay (due to backoff when sensing channel busy)and degraded network throughput.

Consequently, existing frequency allocation mechanisms that do notconsider the combined effect of physical channel and MAC protocol arenot directly applicable to the IEEE 802.11 networks. The MAC CSMAprotocol helps to avoid much of co-channel interference in largemulti-cell IEEE 802.11 networks, but does so at the potential expense ofnetwork performance.

SUMMARY

The invention provides for frequency planning in wireless networks.Traffic load information is obtained for access points belonging to amulti-cell wireless network. Channels are assigned to the access pointsbased on the traffic load information.

Embodiments of the invention may include one or more of the followingfeatures.

The channels may be assigned by determining, for each access point, atleast one set of interferers from among the other access points relativeto the access point. The at least one set of interferers may bedetermined by determining, for each of the other access points, if anyco-channel interference by the other access point is greater than orequal to a detection threshold and, if it is determined that theco-channel interference is greater than or equal to the detectionthreshold, identifying the other access point as belonging to the set ofinterferers for the access point. The detection threshold is indicativeof a busy channel according to the CSMA protocol.

The co-channel interference may be derived from values of signal pathloss between the access point and the other access point andtransmission power of the other access point.

Particular implementations of the invention may provide one or more ofthe following advantages. The frequency planning mechanism serves as avaluable tool for frequency planning of large-scale multi-cell IEEE802.11 WLANs by focusing on interactions among devices such as accesspoints based on their traffic loads and radio propagation. Thus,collision of signals in a frequency band that would otherwise occuramong the APs are minimized or avoided while throughput of informationis optimized. The frequency planning tool can be deployed in a number ofdifferent applications, e.g., as part of managed wireless LAN servicesfor business customers or, alternatively, as part of an access pointproduct for an automatic and adaptive frequency planning.

Other features and advantages of the invention will be apparent from thefollowing detailed description and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is block diagram of a wireless network having multiple accesspoints (APs).

FIG. 2 is a block diagram showing an internal architecture of an APconfigured with a tool for performing a frequency assignment process.

FIG. 3 is an illustration of different classes of co-channel interfererAPs relative to a given AP.

FIG. 4 is a flow diagram of one exemplary embodiment of the frequencyassignment process (of FIG. 2).

FIG. 5 is an illustration of an exemplary frequency assignment producedby the frequency assignment process (of FIG. 4) for a wireless networkwith 7 cells and 21 APs.

FIG. 6 is an illustration of an exemplary frequency assignment producedby the frequency assignment process (of FIG. 4) for a wireless networkwith 37 cells and 111 APs.

DETAILED DESCRIPTION

Referring to FIG. 1, a wireless network 10 includes a wired network 12(e.g., a Local Area Network or “LAN”) having multiple wireless accesspoints 14 coupled thereto. The network 10 further includes wirelessstations or terminals 16 associated with the different APs 14 to forminfrastructure basic service structures (or cells) 18. The AP 14 andterminals 16 served by that AP 14 (collectively referred to as a “cell”)in a given infrastructure basic service set (BSS) 18 communicate witheach other over a common channel that is assigned to the AP. In theembodiment described herein, the AP 14 and terminals 16 communicate witheach other according to the wireless protocol provided by the IEEE802.11 standard. The IEEE 802.11 standard specifies the medium accesscontrol (MAC) and the physical (PHY) characteristics for WLANs. The IEEE802.11 standard is defined in International Standard ISO/IEC 8802-111,“Information Technology-Telecommunications and Information Exchange AreaNetworks,” 1999 Edition, which is hereby incorporated by reference inits entirety. The APs 14 thus provide for communications between theterminals 16 and any devices that may be connected to the wired network12.

Adjacent access points (APs) in IEEE 802.11 networks can be assignedwith the same channel or frequency, which is shared by those APs andtheir associated terminals according to the multiple access protocol(MAC), namely, the Carrier Sensing Multiple Access with CollisionAvoidance (CSMA/CA) protocol. Although the CSMA/CA protocol cancoordinate the bandwidth sharing of the same radio frequency in IEEE802.11 networks, traffic load for the APs has to be considered so thatthere is enough link capacity for the expected traffic load.

In accordance with the present invention, therefore, the network 10employs a frequency planning mechanism that considers the combinedeffects of radio propagation, the IEEE 802.11 MAC protocol and trafficload, so as to mitigate the impact of co-channel interference on theperformance of an IEEE 802.11 network.

Referring to FIG. 2, an exemplary AP 14 is shown. The AP 14 includes aprocessor 20, coupled to the network 12 by way of a network interface22. The network interface 22 permits the processor 20 to send andreceive units of data, such as packets, over the network 12 usingconventional techniques. The processor 20 is also coupled to memory 24.The memory 24 stores firmware 26 that, when executed by the processor20, causes the access point 14 to operate as described herein. Inparticular, when the AP 14 is designated to serve as a “master” AP, thefirmware 26 includes a frequency planning (or assignment) process 28that allows the AP 14 to generate channel assignments for all of the APs14 in the network 10. In an alternative embodiment, with appropriatesynchronization, each AP 14, with its own copy of the frequencyassignment software, could perform the process to determine channelassignment in a distributed manner. Also stored in memory 24 is aparameter store 30 which stores, among other information, APconfiguration 32, including channel assignment information and possiblyAP traffic load information and radio parameter data. The AP 14 can alsoinclude an I/O interface 33 to allow the AP to be connected to otherperipherals.

It will be appreciated that the functionality of the AP 14 may reside ina computer system such as a PC or workstation, with a user interface formanually configuring the access point with information, e.g., channelassignment, or, in the case of the AP running the channel assignmentprocess 28, parameter data to be used by the channel assignment process,or can be connected to a management console for such purpose.

Alternatively, the entire channel assignment process can be installedand executed on a separate system such as a network management system.Once the network management system or AP responsible for the channelassignment has generated the assignment information, AP configurationinformation including the channel assignment can be provided to the APsover the network, or the APs can be configured with the appropriatechannel assignment manually.

The process 28 can be implemented as an automated process that isperformed when an initial site “layout” is being defined. At such astage, the process runs after some pre-determined time interval duringwhich initial loading information is collected. Preferably, it canexecute whenever an access point joins or is removed from the network,or whenever AP loading conditions have changed.

The AP 14 includes a wireless interface 34 that includes one or morewireless transceivers 36. In the described embodiment, the transceivers36 are radio frequency (RF) transceivers. Typically, each transceiver 36includes its own receiver for receiving wireless RF communications froma terminal, a transmitter for transmitting wireless RF communications toa terminal, and a microprocessor to control the transceiver. Wirelesscommunications are received and transmitted by the transceivers 36 viarespective antennas 38, which are connected to the transceiver. Each ofthe transceivers 36 and antennas 38 are conventional in configurationand operation.

Frequency planning for IEEE 802.11 networks has two distinctcharacteristics. First, according to the spectrum allocation in NorthAmerica, there are three overlapping channels for allocation in the IEEE802.11b networks and eight overlapping channels for IEEE 802.11anetworks. Thus, one has to adopt a tight frequency reuse strategy forthe 802.11 networks.

The original IEEE 802.11 specification allows for several differentkinds of physical layers, including direct sequence spread spectrum(DSSS), frequency hopping spread spectrum (FHSS) and infrared (IR). Inparticular, the DSSS design supports data rates of 1 and 2 Mbps.Subsequently, while maintaining backward compatibility to the DSSS802.11, the IEEE 802.11b was adopted to support data rates of 5.5 and 11Mbps, operating in the 2.4 GHz ISM band. As a result, the IEEE 802.11bnetwork can support 1, 2, 5.5 and 11 Mbps, depending on radioconditions. Another extension is IEEE 802.11a, which uses a differentphysical layer known as orthogonal frequency division multiplexing(OFDM) to support data rates ranging from 6 to 54 Mbps, operating in the5.5 GHz band (the U-NII band).

Although the channel assignment technique of the process 28 is describedwith respect to IEEE 802.11b networks, it will be understood that thetechnique can be applied to other IEEE 802.11-based networks as well.The IEEE 802.11 MAC protocol supports the independent basic service set(IBSS), which has no connection to wired networks (i.e., an ad-hocwireless network), as well as an infrastructure BSS, which includes anAP connecting to a wired network (as shown in FIG. 1). While the presentinvention also applies to the IBSS case, only the infrastructure BSSwill be considered.

A brief description of the IEEE 802.11 MAC protocol follows. The IEEE802.11 specification defines five timing intervals for the MAC protocol.Two of them are considered to be basic ones that are determined by thephysical layer: the short interframe space (SIPS) and the slot time. Theother three intervals are defined based on the two basic intervals: thepriority interframe space (PIFS) and the distributed interframe space(DIFS), and the extended interframe space (EIFS). The SIFS is theshortest interval, followed by the slot time. The latter can be viewedas a time unit for the MAC protocol operations, although the IEEE 802.11channel as a whole does not operate on a slotted-time basis. For IEEE802.11b networks (i.e., with a DSSS physical layer), the SIFS and slottime are 10 μs and 20 μs, respectively. The PIFS is equal to SIFS plusone slot time, while the DIFS is the SIFS plus two slot times. The EIFSis much longer than the other four intervals and is used if a data frameis received in error.

The IEEE 802.11 MAC supports the Point Coordination Function (PCF) andthe Distributed Coordination Function (DCF). The PCF providescontention-free access, while the DCF uses the carrier sense multipleaccess with collision avoidance (CSMA/CA) mechanism for contention-basedaccess. The two modes are used alternately in time.

The DCF operates as follows. An AP (or station) with a new packet readyfor transmission senses whether or not the channel is busy. If thechannel is detected idle for a DIFS interval (i.e., 50 μs for IEEE802.11b networks), the AP starts packet transmission. Otherwise, the APcontinues to monitor the channel busy or idle status. After finding thechannel idle for a DIFS interval, the AP: a) starts to treat channeltime in units of slot time, b) generates a random backoff interval inunits of slot time, and c) continues to monitor whether the channel isbusy or idle. In the last step, for each slot time where the channelremains idle, the backoff interval is decremented by one. When theinterval value reaches zero, the AP starts packet transmission. Duringthis backoff period, if the channel is sensed busy in a slot time, thedecrement of the backoff interval stops (i.e., is frozen) and resumesonly after the channel is detected idle continuously for the DIFSinterval and the following one slot time. Again, packet transmission isstarted when the backoff interval reaches zero. The backoff mechanismhelps avoid collision since the channel has been detected to be busyrecently. Further, to avoid channel capture, an AP must wait for abackoff interval between two consecutive new packet transmissions, evenif the channel is sensed idle in the DIFS interval.

The IEEE 802.11 standard requires a receiver to send an acknowledgemessage (ACK) for each packet that is successfully received.Furthermore, to simplify the protocol header, an ACK contains nosequence number and is used to acknowledge receipt of the immediatelyprevious packet sent. That is, APs and stations exchange data based on astop-and-go protocol. The sender is expected to receive the ACK withinthe 10 μs SIFS interval after the packet transmission is completed. Ifthe ACK does not arrive at the sender within a specified ACK—timeoutperiod, or it detects transmission of a different packet on the channel,the original transmission is considered to have failed and is subject toretransmission by the backoff mechanism.

In addition to the physical channel sensing, the IEEE 802.11 MACprotocol implements a network allocation vector (NAV), whose valueindicates to each station the amount of time that remains before thechannel will become idle. All packets contain a duration field and theNAV is updated according to the field value in each decoded packet,regardless of the intended recipient of the packet. The NAV is thusreferred to as a virtual carrier sensing mechanism. The MAC uses thecombined physical and virtual sensing to avoid collision.

The protocol described above is called the two-way handshaking. Inaddition, the MAC also contains a four-way protocol that requires thetransmitter and receiver to exchange Request-to-Send (RTS) andClear-to-Send (CTS) messages before sending actual data, as a way toresolve the so-called hidden terminal problem.

The available number of non-overlapping channels for IEEE 802.11 WLANsystems depends on the underlying PHY layer. In North America, the ISMband at 2.4 GHz is divided into eleven channels for the IEEE 802.11network where adjacent channels partially overlap each other.Nevertheless, among these eleven channels, there are three completelynon-overlapping ones, separated by 25 MHz at their center frequency. Inprinciple, all eleven channels are available for allocation in a givenIEEE 802.11 network. However, it may be that overlapping channels cancause enough interference that it is not beneficial to assignoverlapping channels to APs. Therefore, only the assignment ofnon-overlapping channels is considered. The approach to frequencyplanning described herein can be extended to the allocation ofoverlapping channels with proper weighting of the overlapped spectrum,proportional to their overlaps, however.

The frequency assignment process 28 described herein focuses ontransmission by the APs because the bandwidth consumption for downlink(i.e., from AP to terminal) transmission is much higher than that foruplink (i.e., from terminal to AP) transmission for typical officeenvironment and Internet applications.

The frequency assignment process 28 takes into account the radio-pathsignal loss between every pair of APs in the network 10 and uses thatinformation to define sets or classes of interferers for each i-th AP(or “AP_(i)”). Based on the interferer classification and the expectedtraffic utilization (load) associated with each AP, the effectivechannel utilization as seen by each AP can be determined. The effectivechannel utilization represents the sum of the traffic load of the AP andthat “induced” by its interferers because of channel sensing. In oneembodiment, the problem of frequency planning is formulated as anon-linear zero-one integer programming problem, where one of theobjective functions is to minimize the effective utilization of the“bottleneck” channel (i.e., the AP with the most highly loaded channel).A heuristic algorithm is used to solve the problem.

For a network having M APs, indexed from 1 to M, and in accordance withthe CSMA protocol, an AP with traffic ready for transmission determinesif the assigned channel (frequency) is busy or idle. For example, if theAP detects that the received power of co-channel interference is equalto or greater than a channel-busy detection threshold α (in units ofmW), which corresponds to about −80 dBm in the IEEE 802.11b standard,the channel is considered to be busy. Otherwise, it is idle.

It is possible that the channel busy status is due to a singletransmitting AP or a group of multiple APs transmitting simultaneously.For efficient frequency assignment, the interferers for each AP can beclassified as follows. Specifically, for each AP_(i), C_(i)(1) denotes aset of interfering APs where transmission by any one AP in the set cancause enough interference for AP_(i) to detect channel busy. The APs inthe set C_(i)(1) are called class-1 interferers for AP_(i). Likewise,C_(i)(2) denotes a set of pairs of two interfering APs wheretransmission by any pair of APs in the set can cause AP_(i) to sensechannel busy. The APs in C_(i)(2) are referred to herein as class-2interferers. It can be noted that transmissions by any single AP inC_(i)(2) are not sufficient to cause AP_(i) to sense channel busy.Further, the APs in any AP pair in C_(i)(2) are not class-1 interferersto each other.

Referring to FIG. 3, an example of interferer class definition 40 for agiven AP is shown. The C_(i)(1) and C_(i)(2) interferers for each AP_(i)16 a can be determined by measuring or estimating signal path lossbetween each pair of APs in the network. Letting P_(j) and h_(ij) denotethe transmission power at AP_(j) 16 b and the signal path loss fromAP_(j) to AP_(i), respectively, the classification of AP_(j) 16 b as aC_(i)(1) interferer requires thath_(i)P_(j)≧α.  Eq. (1)47where h_(ij)P_(j) represents, for AP_(i), the co-channel interferencecontributed by AP_(j), (indicated in the figure by reference numeral 42a) and α is the power threshold to detect channel busy.

Similarly, where P_(m) and P_(n) denote the transmission power at AP_(m)16 b and AP_(n) 16 c, respectively, and h_(im) and h_(in) denote thesignal path loss from AP_(m) 16 b to AP_(i) 16 a and AP_(n) 16 c toAP_(i) 16 a, respectively, the pair AP_(m) and AP_(n) belongs toC_(i)(2) ifh _(im) P _(m) +h _(in) P _(n)≧α.  Eq. (2)where h_(im) P_(m)+h_(in) P_(n) represents the co-channel interferenceof the AP pair AP_(m) and AP_(n) (indicated in the figure by referencenumeral 42 b).

It is assumed the transmission power in Equations (1) and (2) is fixedin this disclosure. However, the channel assignment mechanism could beadapted to support dynamic power control as well.

It is possible to define class-3 or even higher classes of interferersas well. Due to the contention-oriented nature of the CSMA protocol,however, the traffic load on each channel (i.e., the probability oftransmission at a given AP) cannot be too high. Thus, the probability ofhaving interferers of class-3, which require simultaneous transmissionat all three interfering APs, is much smaller relative to that of theclass-1 and class-2 interferers. Hence, for simplicity, only class-1 andclass- 2 interferers are considered by the process 28. The process 28also takes into account AP traffic load, denoted generally by ρ.

Measurement of known RF parameters such as transmission power and signalpath loss can be carried out by a dedicated hardware device, such as ahandheld measurement device, or a site survey software tool running on anetwork manager console or PC, or even on the AP device itself. Manywireless LAN equipment vendors bundle such tools with their access pointhardware. Traffic load can also be measured or modeled by commerciallyavailable network management software.

Once measured, modeled or estimated, such parameter data (measurementsor estimates, as discussed above) is stored in the memory 24 for use bythe process 28.

There are a total of N (non-overlapping) channels, indexed by 1 to N,available for allocation. As pointed out above, N=3 for the IEEE 802.11bnetwork for non-overlapping channels. With such a small N, it is assumedthat each AP is assigned one and only one channel. An effective channelutilization U_(i) is defined as the fraction of time at which thechannel can be sensed busy or is used for transmission by AP_(i). Thatis,

$\begin{matrix}{U_{i} = {\rho_{i} + {\sum\limits_{k = 1}{{X_{ik}\left\lbrack {{\sum\limits_{j \in {{Ci}{(1)}}}^{N}{\rho_{j}X_{jk}}} + {\sum\limits_{{({m,n})} \in {{Ci}{(2)}}}{\rho_{m}\rho_{n}X_{mk}X_{nk}}}} \right\rbrack}.}}}} & {{Eq}.\mspace{14mu}(3)}\end{matrix}$where assignment indicator (or weight) X_(ij) is equal to ‘1’ if AP_(i)is assigned with channel_(j) and is equal to ‘0’ otherwise.

Referring to Equation (3) above, the first term ρ_(i) is the offeredtraffic load for AP_(i) in terms of channel utilization withoutinterference from any source. The first summation term inside thebrackets in Equation (3) represents the total traffic load of allclass-1 interfering APs that are assigned the same channel as AP_(i). Asdiscussed earlier, according to the CSMA protocol and because of thedetection threshold α in use, AP_(i) senses channel busy when any one ofits class-1 interferers transmits on the same channel. The lastsummation term in Equation (3) represents the total traffic load of allclass-2 interferers. The interferer classes can be defined to includeoverlapping channels as well. For example, the transmission power frominterferers on overlapping channels can be weighted proportionally tothe spectrum overlap. The weight for non-overlapping channels is ‘0’,and for fully overlapping co-channel cases is ‘1’. Partially overlappingones are somewhere in between depending on their carrier frequencyoffset, filter shapes and other factors.

Channel stability is maintained (i.e., all traffic can be senteventually) by requiring thatU_(i)<S  Eq. (4)for all AP_(i) where i=1 to M, and a threshold S is equal to a valueof 1. The value of S can be made less than 1 to account for overhead ofCSMA contention or other source of interference.

One objective function for the channel assignment is to minimize theeffective utilization of the “bottleneck” AP, that is,minimize max {U₁, U₂, . . . , U_(m)}  Eq. (5)over the assignment indicator {X_(ij)} subject to the constraints ofEquation (4) for all i=1 to M. Clearly, the objective function inEquation (5) is to assign channels such that the effective utilizationof the most heavily loaded AP is minimized. This results in moreresources available for the most heavily loaded AP, given offeredtraffic loads.

In one embodiment, for the channel assignment process 28 with Equation(5) as the objective function, a heuristic algorithm is utilized, asdescribed below with reference to FIG. 4. Thus, the heuristic algorithmattempts to minimize the effective channel utilization for thebottleneck AP. The heuristic algorithm makes use of the followingparameters: offered traffic load p_(i) and interferer sets C_(i)(1) andC_(i)(2) for each AP_(i). Preferably, the process 28 is subject toconstraints of Equation (4) for all APs.

Referring to FIG. 4, the process 28 begins (step 50) by generating arandom (initial) channel assignment for each AP_(i) in the network (step52). This assignment is treated as the best assignment obtained so far.The process 28 determines the effective channel utilization U_(i) foreach AP_(i) based on the generated channel assignment (step 54). Theprocess 28 identifies the AP (say, the “i-th” AP, or AP_(i)) with thehighest or maximum effective channel utilization (step 56). This AP isreferred to as the “bottleneck” AP. The maximum effective channelutilization, that is, max {U_(i)}, for the assignment is denoted by V(step 58). In case of a tie, one such AP_(i) is chosen randomly as the“bottleneck.” For the bottleneck AP_(i), the process 28 identifies itscurrent assigned channel, say channel k (step 60). For each availablechannel n from 1 to N with n≠k and each co-channel AP (say j) inC_(i)(1) (i.e., those APs in the set that have been assigned withchannel k), the process 28 temporarily modifies the channel assignmentby reassigning only AP_(j) with channel n, and recomputes the maximumeffective channel utilization, denoted by W_(jn), for the new assignment(step 62). After completing such testing for all such n and j, theprocess 28 determines the minimum, denoted by W, from among all theW_(jn)'s (step 64). The process 28 compares the values of W and V (step66). If the process 28 determines that the value of W is less than thatof V, then the process 28 replaces V by W, records the associated newassignment as the “new” best solution (i.e., to finalize the channelchange for one AP that minimizes the objective function the most)(step70), and returns to step 54. If, at step 72, the process 28 determinesthat W and V are equal, then, with a pre-specified probability δ,preferably in the range 1>δ>O (to avoid infinite looping, as discussedlater), the process 28 replaces V by W, records the new assignment asthe best solution (step 74) and returns to step 54. If the process 28determines that W is greater than V, the process 28 saves the currentassignment and associated V value as the best solution obtained so far(that is, the current assignment is the local suboptimal assignment)(step 76). The process 28 determines if there is another randomassignment to be considered (step 78). If so, the process 28 returns tostep 52 to repeat the processing for another random assignment. If nofurther random assignments are to be considered, the process 28 selectsa final assignment as the best solution, that is, it is the channelassignment with the lowest value of V, among the local suboptimalassignments reached at step 76 (step 80). The process 28 tests the finalsolution to determine if constraints of Equation (4) for all APs aresatisfied for the final assignment (step 82). If so, the finalassignment is feasible. Otherwise, it is considered that no feasiblesolution exists for the network under consideration. After thefeasibility is tested, the process 28 terminates (step 84).

While the process 28 as illustrated in FIG. 4 may not explicitlyconsider the constraints of Equation (4), minimizing the maximum U_(i)implicitly enhances the chance of satisfying constraints of Equation (4)for all APs.

There are several characteristics of the heuristic assignment techniquethat are worth further consideration. First, it can be shown that theheuristic assignment technique has a loop-free property, that is, with1>δ>O in step 74 (FIG. 4), the heuristic algorithm does not haveinfinite looping. The proof is as follows. Given that the number of AP'sM and available channels N in the system are finite, steps ofidentifying the bottleneck AP and determining W can be completed in afinite amount of time. The only possibility that the algorithm has aninfinite loop is that the steps of processing a random assignment areexecuted repeatedly without stop. Assume, preliminarily, that suchlooping can occur, that the V value after the m-th execution (iteration)is denoted by V_(m), and that δ=0 in step 74. To form the infinitelooping requires that V₁>V₂> . . . >V_(m) with m increasing towardsinfinity. With both M and N being finite, there are only a finite numberof all possible channel assignments. Since each new assignment finalizedby step 70 has a unique maximum effective channel utilization, it isthus impossible that m goes to infinity. That is, step 76 must bereached after a finite amount of processing.

Now assume that infinite looping is possible with 1>δ>0. Based on theabove argument, it is necessary to have V₁> . . . >V_(i)=V_(i+1)> . . .>V_(j)=V_(j+1)> . . . V_(m) with m going to infinity for some i and j.Since the argument above has already ruled out the possibility of havingsubsequences of V_(i)'s of infinite length between two ‘=’ signs on thislist, it must contain an infinite number of ‘=’ signs. Since each ‘=’sign corresponds to an execution of the case of W=V with probability δ,the probability of executing this step for an infinite number of timesis thus zero. Hence, the infinite looping cannot exist.

Although it is possible to treat the case of W=V as reaching a localoptimum (like the case of W>V), numerical experience suggests that thecase of W=V helps explore various assignments for enhanced results,especially when there are multiple bottleneck APs for the channelassignment under consideration.

Since heuristics is involved in the process 28 for the exemplaryalgorithm illustrated in FIG. 4, achieving the optimal solution is notguaranteed. It is possible, however, to quantify the quality of thesuboptimal solution generated by the algorithm. It is observed that theprocessing—in particular, steps 60, 62 and 64 (FIG. 4)—basically testsout various channel assignments to identify a better solution. As thealgorithm is executed for a given initial, random assignment, it ispossible to let Y₀, Y₁, Y₂, . . . , Y_(m), denote the (random) sequenceof the maximum effective channel utilization associated with the channelassignments under testing by step 62, with Y₀ denoting the quantity forthe initial, random assignment. Based on the Y_(i) sequence, anothersequence Z₀, Z₁, Z₂, . . . , Z_(n) is constructed as follows: (i)initialize with Z₀=Y₀ and set i=0; (ii) for each j=1, 2, . . . , m,compare Y_(j) with Z_(i); and (iii) if Z_(i)>Y_(j), then set i=i+1 andZ_(i)=Y_(j); otherwise, repeat (ii) for the next j value.

In essence, the sequence Z_(i) is constructed by examining Y_(j) one byone, starting with Z₀=Y₀ and adding Y_(j) as the last element in theZ_(i) sequence only if Y_(j) is less than Y_(i) for all i<j (orequivalently, Y_(j) is less than Z_(i), the last element in the currentsequence). Clearly, the sequence Z_(i) is monotonic strictly decreasing.Physically, Z_(i) represents the sequence of the maximum effectivechannel utilization for an improved assignment finalized by step 70, orstep 74 (FIG. 4) that yields a maximum utilization lower than anyassignments examined by the algorithm so far in the search process.

The algorithm is repeated for a given number (say K) of initial randomassignments. For each initial assignment, one such sequence Z_(i) (asdiscussed above) can be obtained. It can be noted that the sequencesassociated with different initial assignments have different lengths andare mutually independent of each other (although elements in the samesequence are dependent). Furthermore, when the algorithm eventuallystops, it is assumed that it has encountered a total of n improvedassignments (i.e., improved over those examined earlier and derived fromthe same initial assignment), which is the sum of lengths of thesequences of Z_(i) minus K.

One can view that the maximum effective channel utilization for allpossible assignments for the given network has a probabilitydistribution. Allowing T_(π) to be the maximum utilization for thetop-π-fraction of assignments (e.g., the top 0.001 percentileassignments), a random assignment with its maximum utilization Z₀, givesP[Z ₀ ≦T ₉₀]=π  Eq. (6)It can be proven that, if the algorithm has encountered a total of nimproved assignments at the completion of its execution, thenQ _(π)> 1−(1−π)^(n+1)  Eq. (7)where Q_(π) denotes the probability that the final suboptimal solutiongenerated by the algorithm falls within the top-π-fraction ofassignments. The proof is as follows. First, the case of encountering nimproved assignments for one initial, random assignment is examined. Bydefinition,

$\begin{matrix}{Q_{\pi} = {{P\left\lbrack {{\min\limits_{i}Z_{i}} \leq T_{\pi}} \right\rbrack} = {1 - {{P\left\lbrack {{\min\limits_{i}Z_{i}} > T_{\pi}} \right\rbrack}.}}}} & {{Eq}.\mspace{14mu}(8)}\end{matrix}$The event of (min Z_(i)>T_(π)) in the above is identical to havingZ₀>T_(π), Z₁>T_(π), . . . , and Z_(n)>T_(π). Given that Z_(i) is astrictly decreasing (random) sequence, thenP[Z ₀ >T _(π) ΛZ ₁ >T ₉₀ Λ . . . ΛZ _(n) >T _(π) ]<P[Z ₀ >T _(π) ΛZ _(o)¹ >T _(π) Λ . . . ΛZ _(o) ^(n) >T _(π)]  Eq. (9)where Z₀ ^(i) is a random variable independently drawn from the samedistribution for Z_(o) for i=1 to n. One can obtain Equation (9) byreplacing Z_(i) on the left hand side by Z₀ ^(i) on the right side forone i at a time. Since the Z₀ ^(i) variables are independent,P[Z ₀ >T _(π) ΛZ ₀ ¹ >T _(π) . . . Z _(o) ^(n) >T _(π) ]={P[Z _(o) >T_(π)]}^(n+1)  Eq. (10)

Using the definition in Equation (6), substituting Equation (10) intoEquation (9) and then Equation (9) into Equation (8) yields Equation(7). The case with multiple initial random assignments is proved byexploiting the property that the sequences Z_(i) associated withdifferent initial assignments are mutually independent.

The performance of the process 28 is validated by applying the process28 to two settings of multi-cell networks using the IEEE 802.11 airinterface for which the optimal assignment is known. The settingscorrespond to settings for a seven (7) cell network and thirty-seven(37) cell network.

Referring to FIG. 5, an assignment 90 generated by the process 28 for asetting that corresponds to a network with 7 cells is shown. Threeadjacent hexagon-shaped sectors 92 a, 92 b and 92 c form a cell 94. Eachsector 92 is served by an AP at the center of the cell. Each AP antennahas a beamwidth of 60′ and points toward an appropriate direction toserve the associated sector. Thus, there are 21 APs in the 7 cellnetwork, with 3 APs for each given cell co-located at the cell center,indicated by reference numeral 96.

Similarly, and referring to FIG. 6, an assignment 100 for a setting thatcorresponds to a network with 37 cells is shown. Three adjacenthexagon-shaped sectors 102 a, 102 b and 102 c form a cell 104. For thissetting, there are 111 APs, with 3 APs for each given cell co-located atthe cell center, indicated by reference numeral 106.

The antenna gain has a parabolic shape; that is, a 3 dB drop relative tothe front direction occurs at the half beamwidth angle. Any directionbeyond a threshold angle in clockwise or anti-clockwise directionsuffers a given, fixed attenuation relative to the gain at the frontdirection, which is called the front-to-back (FTB) ratio. The FTB is setto be 25 dB.

It may be recalled that only the AP-to-AP interference is considered inthe current formulation. The radio link between any pair of APs in thenetwork is characterized by a path-loss model with an exponential of3.5. Cell radius is assumed to be 1 Km and the path loss at 100 m fromthe cell center is −73 dB. Transmission power for each AP antenna is 30dBm (or 1 W). All APs have an identical amount of offered traffic. Itwill be noted that the solution generated by the process 28 in thisinstance does not depend on the actual traffic load, but the feasibilityof the final solution does. In order to ensure that the optimalassignment is known, shadowing and fast fading are not considered. Inaddition, the channel-busy detection threshold α is set to be 2.5 e–3 μW(which corresponds to −86 dBm). As pointed out earlier, there are 3non-overlapping channels available in the ISM band for assignment. Basedon the parameter settings for both 7 and 37 cell networks, the optimalassignment is the traditional frequency reuse of 3. That is, no adjacentsectors (APs) use the same channel.

When the process 28 is applied to the network with 7 cells and 21 APs,as shown in FIG. 5, it generates the optimal channel assignment based on50 random assignments. The optimal assignment 90 with channels 1 to 3assigned to the various sectors 92 a, 92 b and 92 c for each cell 94 isas shown in FIG. 5.

As for the network with 37 cells and 111 APs, the process 28 was unableto yield the obvious optimal assignment of reuse of 3, that is, withoutconsidering the boundary effect of the cell layout (which makes theinterference conditions non-uniform). The suboptimal solution forchannels 1–3 obtained from the process using 1,000 random assignments isthe assignment 100 shown in FIG. 6. It can be seen from the assignment100 that most of the sectors (APs) use a channel different from those inadjacent sectors. In the worst case, at most two adjacent sectors sharethe same channel. The process encountered and finalized a total of505,363 improved assignments. Based on the analysis set forth above,with a probability higher than 99.4%, the suboptimal solution,assignment 100, falls within the top 0.001th percentile. This result isquite acceptable.

The above two examples have uniform traffic load and uniform propagationenvironments with obvious solutions and are only used to verify thecorrectness of the algorithm. However, for any wireless network ofconsiderable size, the traffic load and the propagation environment areseldom uniform and are usually without obvious channel assignmentsolutions. The approach of the frequency planning process 28 can easilyproduce a good (albeit suboptimal) channel assignment solution in suchcases, with provable closeness to the optimal solution. Also, if thetraffic load is slowly fluctuating over time, the approach can be usedto generate a series of channel assignments over time to bestaccommodate the changing conditions.

Other objective functions can be used in the channel assignmentoptimization. For example, another objective function (in addition toobjective function of Equation (5)) is to minimize the overallinterference, that is,

$\begin{matrix}{{minimize}\mspace{14mu}{\sum\limits_{i = 1}^{M}U_{i}}} & (11)\end{matrix}$over the assignment indicator {X_(ij)} subject to the constraints ofEquation (4) for all i=1 to M. It can be noted that the sum of all U_(i)reflects the total effective channel utilization. Minimizing the sumtends to minimize the overall interference in the network whilemaintaining stability of each channel shared and detectable by multipleneighboring APs.

For the optimization with Equation (11) as the objective function, alinear integer programming approach can be used. For a given networksetting, the offered load p_(i) and the interferer sets C_(i)(1) andC₁(2) for each AP_(i) are known. The programming problem is non-lineardue to the cross-products of X_(ij)'s in U_(i), as defined in Equation(3). Using known techniques—for example, the technique described in thepaper by W. W. Chu entitled “Optimal File Allocation in a MultipleComputer System, “IEEE Trans. On Computers, C-18, No. 10, pp. 885–889,Oct. 1969—it is possible to linearize the problem by replacingX_(ik)X_(mk)X_(nk) by a new term Y_(ikmn). Similarly, the termX_(ik)X_(jk) is replaced by a new term Z_(ikj). The resultant problembecomes a linear integer programming problem, which has been shown to beNP-complete.

Yet another objective function is to maximize network throughput.

Other embodiments are within the scope of the following claims. Forexample, the above-described approach may be extended to consider one ormore of the following: non-uniform transmission power by the APs;upstream traffic; overlapping channels (as discussed earlier); real-timeadaptive channel assignment to meet the fluctuation of traffic load atvarious APs over time; inclusion of path gains for stations; and specialfrequency constraints for individual AP's (e.g., AP closest to aMicrowave, WLANs of other carriers).

1. A method for frequency planning in wireless networks comprising:obtaining traffic load information for access points belonging to awireless network having a plurality of Access Points (APs) where achannel between a terminal and an AP of said network is employed tocommunicate both traffic and control information and communication isestablished between said terminal and said AP by use of a protocol thatsupports a Point Coordination Function (PCF) that providescontentions-free access, and a Distributed Coordination Function (DCF)that uses a carrier sense multiple access with collision avoidance(CDMA/CA) mechanism for contention-based access; and assigning channelsto the access points based on the traffic load information where trafficload information for a considered AP includes load of traffic betweenthe considered AP and terminals that communicate with the considered AP,and effective load that results from detections of channel busyconditions due to interfering communication by terminals with other APsof said network, wherein the step of assigning comprises: determining,for each considered AP, at least one set of interferers from among theother APs relative to said considered AP based on interference signalstrength; generating random channel assignments for the access points;determining effective channel utilization values for each access point;modifying the random channel assignment for interferers in the at leastone set of interferers such that the highest one of the effectivechannel utilization values is minimized; repeating said step ofmodifying until the highest one of the effective channel utilizationvalues cannot be reduced by further modification; and saving themodified random channel assignment as a final assignment.
 2. The methodof claim 1 wherein the step of determining comprises: determining, foreach of the other access points, if any co-channel interference by anyof the other access points is greater than or equal to a detectionthreshold, the detection threshold indicative of an additional perceivedload arising from the CSMA protocol; and if it is determined that theco-channel interference is greater than or equal to the detectionthreshold, identifying the other access point as belonging to the set ofinterferers for the access point that increases the load that isconsidered to burden the access point.
 3. The method of claim 2 whereinthe co-channel interference between an access point and another accesspoint is derived from values of signal path loss between the accesspoint and the other access point and transmission power of the otheraccess point.
 4. The method of claim 2 wherein the at least one set ofinterferers comprises a second set of interferers, and wherein the stepof determining comprises: determining, for any pair of the other accesspoints, if any combined co-channel interference by such pair is greaterthan or equal to a detection threshold, the detection thresholdindicative of an additional perceived load arising from the CSMAprotocol; and if it is determined that the combined co-channelinterference is greater than or equal to the detection threshold,identifying the other access points in such pair as belonging to thesecond set of interferers for the access point that increases the loadthat is considered to burden the access point.
 5. The method of claim 1wherein the step of assigning further comprises: providing the finalassignment to the access points.
 6. The method of claim 1 wherein thestep of assigning further comprises: assigning randomly a channel toeach of the access points; and computing, based on the random channelassignment, an effective channel utilization value for each accesspoint, the effective channel utilization value representing the sum ofan offered load associated with the access point and total traffic loadassociated with each set of interferers.
 7. The method of claim 6wherein the step of assigning further comprises: determining whichaccess point has the highest effective channel utilization value;identifying which channel is assigned to the access point having thehighest effective channel utilization value; and for each access pointin the first set of interferers, modifying the random channelassignment; recomputing the effective channel utilization value for themodified random channel assignment; and repeating modifying andrecomputing for each available channel other than the channel assignedto the access point having the highest effective channel utilizationvalue; determining a minimum effective channel utilization from amongthe recomputed effective channel utilization values; comparing theminimum effective channel utilization and the recomputed effectivechannel utilization values; and replacing the highest effective channelutilization with the determined minimum effective channel utilizationand saving the modified random channel assignment as a best solution ifthe determined minimum effective channel utilization is lower than thehighest effective channel utilization.
 8. The method of claim 7 whereinthe step of assigning further comprises: with a pre-specifiedprobability, replacing the highest effective channel utilization withthe determined minimum effective channel utilization and saving themodified random channel assignment as a best solution if the determinedminimum effective channel utilization is equal to the highest effectivechannel utilization.
 9. The method of claim 1 wherein the step ofassigning further comprises: computing an effective utilization valuefor each access point based on the final assignment; and determining ifthe effective utilization value for each access point is less than avalue of one.
 10. The method of claim 9, where the effective utilizationof a channel by an access point is a sum of channel utilization by saidaccess point, plus interference in said channel by units belonging to afirst class of interferers, plus interference in said channel by unitsbelonging to a second class of interferers, where said units in saidfirst class are characterized by an interference level that issufficiently high to cause a conclusion that said channel is busy, andsaid units in said second class are characterized by an interferencelevel that requires two of the second class units to transmitconcurrently to cause a conclusion that said channel is busy.
 11. Themethod of claim 1 wherein the channels comprise non-overlappingchannels.
 12. The method of claim 1 wherein the channels compriseoverlapping and non-overlapping channels.
 13. The method of claim 1wherein the access points employ the CSMA/CA protocol.
 14. The method ofclaim 1 wherein the step of assigning comprises: seeking to minimizeeffective channel utilization of a most heavily loaded of the accesspoints.
 15. The method of claim 1 wherein the step of assigningcomprises: seeking to minimize total effective channel utilization ofall access points.
 16. The method of claim 1 wherein the step ofassigning comprises: seeking to maximize network throughput.
 17. Themethod of claim 1 where multiple access protocol is able to carrycommunication in frequency bands centered about 1.9 GHz, or 5.4 GHz, fora link distance of at most several hundred meters.
 18. The method ofclaim 1 where the step of assigning executes a process that minimizeschannel utilization by an AP, where channel utilization corresponds tothe fraction of time at which the channel can be sensed busy or is usedfor transmission.
 19. An article comprising: a storage medium havingstored thereon instructions that when executed by a machine result inthe following: obtaining traffic load information for access pointsbelonging to a wireless network having a plurality of Access Points(APs) where a channel between a terminal and an AP of said network isemployed to communicate both traffic and control information andcommunication is established between said terminal and said AP by use ofmultiple access protocol; and assigning channels to the access pointsbased on the traffic load information where traffic load information fora considered AP includes load of traffic between the considered AP andterminals that communicate with the considered AP, and effective loadthat results from detections of channel busy conditions due tointerfering communication by terminals with other APs of said network,wherein the step of assigning comprises: determining, for eachconsidered AP, at least one set of interferers from among the other APsrelative to said considered AP based on interference signal strength;generating random channel assignments for the access points; determiningeffective channel utilization values for each access point; modifyingthe random channel assignment for interferers in the at least one set ofinterferers such that the highest one of the effective channelutilization values is minimized; repeating said step of modifying untilthe highest one of the effective channel utilization values cannot bereduced by further modification; and saving the modified random channelassignment as a final assignment.
 20. An apparatus comprising: aprocessor; and a memory storing a computer program product residing on acomputer-readable medium comprising instructions to cause a computer to:obtain traffic load information for access points belonging to amulti-cell IEEE 802.11-type wireless network; and assign channels to theaccess points based on the traffic load information where traffic loadinformation for a considered AP includes load of traffic between theconsidered AP and terminals that communicate with the considered AP, andeffective load that results from detections of channel busy conditionsdue to interfering communication by terminals with other APs of saidnetwork, wherein the step to assign channels to the access pointscomprises: determining, for each considered AP, at least one set ofinterferers from among the other APs relative to said considered APbased on interference signal strength; generating random channelassignments for the access points; determining effective channelutilization values for each access point; modifying the random channelassignment for interferers in the at least one set of interferers suchthat the highest one of the effective channel utilization values isminimized; repeating said step of modifying until the highest one of theeffective channel utilization values cannot be reduced by furthermodification; and saving the modified random channel assignment as afinal assignment.
 21. An access point for use in wireless networkcomprising: a logic module configured to obtain traffic load informationfor access points belonging to the wireless network having a pluralityof Access Points (APs) where a channel between a terminal and an AP ofsaid network is employed to communicate both traffic and controlinformation and communication is established between said terminal andsaid AP by use of multiple access protocol; and a logic moduleconfigured to assign channels to the access points based on the trafficload information where traffic load information for a considered APincludes load of traffic between the considered AP and terminals thatcommunicate with the considered AP, and effective load that results fromdetections of channel busy conditions due to interfering communicationby terminals with other APs of said network, wherein assigning channelsto the access points comprises: determining, for each considered AP, atleast one set of interferers from among the other APs relative to saidconsidered AP based on interference signal strength; generating randomchannel assignments for the access points; determining effective channelutilization values for each access point; modifying the random channelassignment for interferes in the at least one set of interferers suchthat the highest one of the effective channel utilization values isminimized; repeating said step of modifying until the highest one of theeffective channel utilization values cannot be reduced by furthermodification; and saving the modified random channel assignment as afinal assignment.